{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "from math import ceil\n",
    "from sklearn.metrics import accuracy_score, log_loss\n",
    "import torch\n",
    "from torch.utils.data import DataLoader\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "import sys\n",
    "sys.path.append('..')\n",
    "from utils.input_pipeline import get_image_folders\n",
    "from utils.diagnostic import top_k_accuracy, count_params,\\\n",
    "    entropy, model_calibration, predict\n",
    "\n",
    "torch.cuda.is_available()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from get_densenet import get_model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "_, val_folder = get_image_folders()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "model, _, _ = get_model()\n",
    "\n",
    "# load pretrained quantized model\n",
    "model.load_state_dict(torch.load('model_ternary_quantization.pytorch_state'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "440264"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# number of params in the model\n",
    "count_params(model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Show some quantized kernel tensors (there are 62 such kernels overall)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# all quantized kernels\n",
    "all_kernels = [\n",
    "    (n, p.data) for n, p in model.named_parameters() \n",
    "    if ('denseblock' in n or 'transition' in n) and 'conv' in n\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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9bPBlm1mzRMRtgBoMPrqH8QN4X4NpLQAWNK86MzMz60s/zmrzZ3azNtJnI1zSYtIRsXGS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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff263a5b320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# show distribution of weights in kernels that are in the beginning of the network \n",
    "_, axes = plt.subplots(nrows=6, ncols=4, figsize=(14, 10))\n",
    "axes = axes.flatten()\n",
    "for i, (name, kernel) in enumerate(all_kernels[:24]):\n",
    "    axes[i].hist(kernel.cpu().numpy().reshape(-1));\n",
    "    axes[i].set_title(name[9:-7]);\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Ps17V7n1etfwuqnquvySGrJNyvqjd52Ivatc+r1reVznXOzm/ndNWdT5HO1ip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\nDMq8+QUGj5EAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff264ad7ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# kernels in the end of the network \n",
    "_, axes = plt.subplots(nrows=6, ncols=4, figsize=(14, 10))\n",
    "axes = axes.flatten()\n",
    "for i, (name, kernel) in enumerate(all_kernels[-24:]):\n",
    "    axes[i].hist(kernel.cpu().numpy().reshape(-1));\n",
    "    axes[i].set_title(name[9:-7]);\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# sparcity distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "sparcity = []\n",
    "for n, p in all_kernels:\n",
    "    sparcity.append(p.eq(0.0).float().mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Hrqyq73WH/r7IcsFv5f4c3yaffNjG8kmDHfzg5MMzVixzOssfhpNXzD8OeGw3vR24h1VO\nWG1hzpNHpl8J7O2mn8GjT+Ldz+adxOuTc+5QLpZPBj0AHD+tnCuWv5YfnGycqf25Rs6Z2p/AU0am\nfwm4vps+HvhS93k6rpuexZyz9nnfCVw6kucrwI9t5f6c6J9t0zcAL2f5f93uA97WzftDlkfjAP8I\nfB24pXtc2c1/HnBbt7NvAy6ccs73AXd0GT89+h8Ay//v4j7gbuBls5gTOHtk/k3AK6eZc8Wy19IV\n5aztz8PlnLX9Cfxxl+fW7t/7T46s+1qWTy7fC7xmFnPO4Oc9LB9uu7PLc8409ue4D68UlaRGzMxJ\nUUlSPxa6JDXCQpekRljoktQIC12SGmGhS1IjLHRJaoSFLkmN+F9aO5lo1tbtdgAAAABJRU5ErkJg\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff263850a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(sparcity);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.37555713999655937"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(sparcity)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# scaling factors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "upper_scaling_factor = []\n",
    "lower_scaling_factor = []\n",
    "for n, p in all_kernels:\n",
    "    upper_scaling_factor.append(p.max())\n",
    "    lower_scaling_factor.append(p.min())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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F4FHgu8BZ8655gr78afd7cT9wJ/Daedc8oB83AIeB/+5+T64EPgB8oFsfVv8znce6n6mB\nV73N+9GjL1ev+UzuBt44zf17p6gkNWJTD7lIkv6PgS5JjTDQJakRBrokNcJAl6RGGOiS1AgDXZIa\nYaBLUiP+BzzTqeTnw7alAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff263850ef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(upper_scaling_factor);\n",
    "plt.hist(lower_scaling_factor);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Error analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### get all predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "val_iterator_no_shuffle = DataLoader(\n",
    "    val_folder, batch_size=64, shuffle=False\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 157/157 [00:04<00:00, 31.61it/s]\n"
     ]
    }
   ],
   "source": [
    "val_predictions, val_true_targets = predict(model, val_iterator_no_shuffle)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### logloss and accuracies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.6909839675559515"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "log_loss(val_true_targets, val_predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.39610000000000001"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(val_true_targets, val_predictions.argmax(1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.51990000000000003, 0.59089999999999998, 0.63590000000000002, 0.67230000000000001, 0.77500000000000002]\n"
     ]
    }
   ],
   "source": [
    "print(top_k_accuracy(val_true_targets, val_predictions, k=(2, 3, 4, 5, 10)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### number of misclassified images (there are overall 10000 images in the val dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6039"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hits = val_predictions.argmax(1) == val_true_targets\n",
    "(~hits).sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### entropy of predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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IBCncRUQiSOEuIhJBCncRkQhSuIuIRJDCXUQkghTuIiIRpHAXEYkghbuISAQp3EVEIkjh\nLiISQQp3EZEIUriLiESQwl1EJIJChbuZDTWzTWa22cymHKLNv5pZuZltMLOnk1umiIjUR+u6GphZ\nBvAgcDZQCZSYWbG7l8e16QHcBAxw98/N7MjGKlhEROoWpud+MrDZ3d93993AM8DIam2uAh50988B\n3H1rcssUEZH6CBPunYEtccuVwbp4xwHHmdn/MbM1ZjY0WQWKiEj91TksU4/t9AAGA12AFWbW292/\niG9kZlcDVwMcc8wxSdq1iIhUF6bn/hHQNW65S7AuXiVQ7O573P0D4B1iYX8Ad5/t7gXuXpCdnZ1o\nzSIiUocw4V4C9DCz7mbWFrgQKK7W5kVivXbMrBOxYZr3k1iniIjUQ53h7u57gUnAIuBt4Fl332Bm\n082sMGi2CNhuZuXAMmCyu29vrKJFRKR2ocbc3X0hsLDauqlxjx24PvgjIiIppl+oiohEkMJdRCSC\nFO4iIhGkcBcRiSCFu4hIBCncRUQiSOEuIhJBCncRkQhSuIuIRJDCXUQkghTuIiIRpHAXEYkghbuI\nSAQp3EVEIkjhLiISQQp3EZEIUriLiESQwl1EJIIU7iIiEaRwFxGJIIW7iEgEKdxFRCJI4S4iEkEK\ndxGRCFK4i4hEkMJdRCSCFO4iIhGkcBcRiSCFu4hIBCncRUQiKFS4m9lQM9tkZpvNbEot7f67mbmZ\nFSSvRBERqa86w93MMoAHgZ8AvYCxZtarhnYdgeuA15NdpIiI1E+YnvvJwGZ3f9/ddwPPACNraPc/\ngLuAXUmsT0REEhAm3DsDW+KWK4N1VcysL9DV3f93EmsTEZEENfiEqpm1Au4B/j1E26vNrNTMSrdt\n29bQXYuIyCGECfePgK5xy12Cdft1BHKA5WZWAZwKFNd0UtXdZ7t7gbsXZGdnJ161iIjUKky4lwA9\nzKy7mbUFLgSK9z/p7jvcvZO7d3P3bsAaoNDdSxulYhERqVOd4e7ue4FJwCLgbeBZd99gZtPNrLCx\nCxQRkfprHaaRuy8EFlZbN/UQbQc3vCwREWkI/UJVRCSCFO4iIhGkcBcRiSCFu4hIBCncRUQiSOEu\nIhJBoS6FTEdXFJWEavfohH6NXImISNNTz11EJIIU7iIiEaRwFxGJIIW7iEgERfaEalhhTrzqpKuI\npJsWH+5h6AtARNKNwl2kOVn223DtzripceuQtKcxdxGRCFLPXaQphO2RiySJeu4iIhGknrtIQzT3\nHrnG8FsshbtITZp7aIvUQeHehHRJpYg0FY25i4hEkHruIulIw0ZSB4W7tBwKRGlBNCwjIhJB6rlL\n00t2D1qX8YkcROGeJGFv69dU2wFdeSPSkmlYRkQkgtRzl/SnE6UiB1HPXUQkghTuIiIRpGEZEanf\n0JauTkoLoXruZjbUzDaZ2WYzm1LD89ebWbmZrTezJWb2o+SXKiIiYdXZczezDOBB4GygEigxs2J3\nL49rtg4ocPedZvZz4H8CYxqjYGl6oSc804lNkWYjTM/9ZGCzu7/v7ruBZ4CR8Q3cfZm77wwW1wBd\nklumiIjUR5hw7wxsiVuuDNYdyhXAH2t6wsyuNrNSMyvdtm1b+CpFRKReknpC1cwuAQqAQTU97+6z\ngdkABQUFnsx9y8GS+WtXEUkvYcL9I6Br3HKXYN0BzOws4BZgkLt/m5zyREQkEWHCvQToYWbdiYX6\nhcBF8Q3MrA/wMDDU3bcmvUppFIWfPx6qXfEPx9fZ5oqiEgo/P+g7/yAj82sb0RORZKkz3N19r5lN\nAhYBGcBcd99gZtOBUncvBu4GDgPmmxnAh+5e2Ih1SxMK+yUgIs1HqDF3d18ILKy2bmrc47OSXJeI\niDSAfqEqIvUT9vcM+iVrSincI6a5D6G8VKZxeZGmoHCXZkdfACINp1khRUQiSOEuIhJBGpaRtBRm\n6CYMDe80Ip14TSmFe5po7idKo07nASTdaFhGRCSCFO4iIhGkYZkU03BLaiVr7D7stjR0I01FPXcR\nkQhSuIuIRJDCXUQkgjTmLtKENC5fA10P3ygU7o1EJ0pFJJU0LCMiEkEKdxGRCNKwjEgzo3F5SQaF\nu4ikB514rRcNy4iIRJB67vWkq2BEJB0o3EXSUNg5cTQ233JpWEZEJILUcxeJMF1503Ip3AMaS5eW\nSl8A0RT5cFdoi7QwumQSaAHhLiINp959+lG4i0hS6AugeUnLcNdQi0h60iWcTSctw11EpMEiPjYf\nKtzNbCjwOyADmOPud1Z7/nvAE8BJwHZgjLtXJLdUEWkpNMTTcHWGu5llAA8CZwOVQImZFbt7eVyz\nK4DP3f1fzOxC4C5gTGMULCIC+gKoS5ie+8nAZnd/H8DMngFGAvHhPhKYFjxeADxgZubunsRaRUTq\nJSlfAGGHb6BZDeGECffOwJa45UrglEO1cfe9ZrYDOAL4NBlFioikhWY0jt+kJ1TN7Grg6mDxazPb\nlOCmOhGNL44oHIeOoXmIwjFANI4jxDHc3JDt/yhMozDh/hHQNW65S7CupjaVZtYayCJ2YvUA7j4b\nmB2msNqYWam7FzR0O6kWhePQMTQPUTgGiMZxNJdjCDMrZAnQw8y6m1lb4EKguFqbYmB88HgUsFTj\n7SIiqVNnzz0YQ58ELCJ2KeRcd99gZtOBUncvBh4FnjSzzcBnxL4AREQkRUKNubv7QmBhtXVT4x7v\nAkYnt7RaNXhop5mIwnHoGJqHKBwDROM4msUxmEZPRESiR3diEhGJoLQLdzMbamabzGyzmU1JdT2J\nMLO5ZrbVzN5KdS2JMLOuZrbMzMrNbIOZXZfqmhJhZplmttbM3gyO47ZU15QoM8sws3Vm9nKqa0mE\nmVWY2V/NrMzMSlNdT6LM7AdmtsDMNprZ22Z2WspqSadhmWAqhHeImwoBGFttKoRmz8wGAl8DT7h7\nTqrrqS8zOwo4yt3/YmYdgTeA89LwczCgg7t/bWZtgFXAde6+JsWl1ZuZXQ8UAN939xGprqe+zKwC\nKHD3tL7G3cweB1a6+5zg6sL27v5FKmpJt5571VQI7r4b2D8VQlpx9xXEripKS+7+sbv/JXj8FfA2\nsV8ppxWP+TpYbBP8SZ/eTsDMugDDgTmprqUlM7MsYCCxqwdx992pCnZIv3CvaSqEtAuVKDGzbkAf\n4PXUVpKYYDijDNgKvOru6Xgc9wE3At+lupAGcOAVM3sj+CV7OuoObAMeC4bI5phZh1QVk27hLs2I\nmR0GPAf8m7t/mep6EuHu+9w9n9gvr082s7QaJjOzEcBWd38j1bU00I/dvS/wE+AXwdBlumkN9AUe\ncvc+wDdAys4Lplu4h5kKQZpAMEb9HPCUuz+f6noaKvjn8zJgaKprqacBQGEwZv0McKaZ/VdqS6o/\nd/8o+O9W4AViQ7DpphKojPvX3wJiYZ8S6RbuYaZCkEYWnIh8FHjb3e9JdT2JMrNsM/tB8LgdsRP1\nG1NbVf24+03u3sXduxH7/2Gpu1+S4rLqxcw6BCfmCYYxzgHS7koyd/+/wBYzOz5YNYQDp0ZvUml1\nm71DTYWQ4rLqzcx+DwwGOplZJXCruz+a2qrqZQAwDvhrMF4NcHPwS+Z0chTweHAVVivgWXdPy0sJ\n09w/AS/E+gy0Bp529z+ltqSEXQM8FXQ+3wcuS1UhaXUppIiIhJNuwzIiIhKCwl1EJIIU7iIiEaRw\nFxGJIIW7iEgEKdylyZjZeWbWK9V17Gdmvzez9Wb2y0bezzQzuyF4PN3Mzqqlbb6ZDYtbLkzX2U8l\ntdLqOndJe+cBL1PDDzvMrLW7722qQszsvwH93P1fEnx9QvXG38HsEPKJze64MGhfjH6oJwlQz10S\nZmaXBPOhl5nZw8GPgTCzr83sN8E86WvM7J/MrD9QCNwdtP9nM1tuZvcF83dfZ2bdzGxp0JteYmbH\nBNsrMrNZZlZqZu8E86lgZivMLD+unlVmlletxkwzeyyYK3ydmZ0RPPUK0Dmo5fRqrznU/iaYWbGZ\nLQWWBOsmm1lJUPNtcdu4JXjtKuD4atseFTzuZ2avBe/T2mBWwenAmKCuMcE+Hwja1/b+3B9s6/24\n7R8VvEdlZvZW9eOUaFO4S0LM7ARgDDAgmHhrH3Bx8HQHYI275wErgKvc/TViPdDJ7p7v7u8Fbdu6\ne4G7/y9gJvC4u+cCTwH3x+2yG7H5RoYDs8wsk9gUCBOCeo4DMt39zWql/oLY7L69gbHEfpGaSeyL\n5r2glpU1HGJN+4PYXCGj3H2QmZ0D9Aja5QMnmdlAMzuJ2FQA+cAwoF8N719bYB6x+ePzgLOITTQ1\nFZgX1DWv2stqe3+OAn4MjADuDNZdBCwKPp88oAxpMRTukqghwElASTAFwRDg2OC53cSGXyB2I49u\ntWwnPsBOA54OHj9JLKz2e9bdv3P3d4n9rLsnMB8YEUxidjlQVMP2fwz8F4C7bwT+BhxX9+HVuD+I\nTQu8fy7+c4I/64C/BG16AKcDL7j7zmC2zJqGVY4HPnb3kqC2L0MM89T2/rwY1FtO7Of8EJuL6TIz\nmwb0DubelxZCY+6SKCPWi7yphuf2+P+f12Iftf89+ybk/qrPk+HuvtPMXiV2w5Z/JfZlkywH7S/4\nb3y9BvzW3R+Ob2hm/5bEOsL6Nr4EiN0UxmJT5w4HiszsHnd/IgW1SQqo5y6JWgKMMrMjAczscDP7\nUR2v+QroWMvzrxEbzoDYEE/8cMloM2tlZv9M7F8Im4L1c4gNT5S4++c1bHNlsK39QzfHxL22Nofa\nX7xFwOUWm9ceM+scvB8rgPPMrJ3FZjv8aQ2v3QQcZWb9gtd2NLPW1P4e1fb+HCT4PD5x90eIvU8p\nm35Wmp567pIQdy83s/8gdvecVsAeYuPbf6vlZc8Aj5jZtcCoGp6/hthdbCYTu6NN/Ix6HwJrge8D\nE919V1DHG2b2JfDYIfb5n8BDZvZXYC8wwd2/tdgMhLU5aH/VX+PurwTnHlYHz30NXBLcW3Ye8Cax\nOzyVVN+4u+82szHATItNN/wPYuPuy4ApwVDXb+vx/tRkMDDZzPYEtV1a10FLdGhWSGn2zKwIeNnd\nF9Tw3NHAcqCnuyflNnO17U8kXWhYRtKWmV1K7N6ttyQr2EWiQj13EZEIUs9dRCSCFO4iIhGkcBcR\niSCFu4hIBCncRUQiSOEuIhJB/w8p+7o32BZ7TAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff26056e940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(\n",
    "    entropy(val_predictions[hits]), bins=30, \n",
    "    normed=True, alpha=0.7, label='correct prediction'\n",
    ");\n",
    "plt.hist(\n",
    "    entropy(val_predictions[~hits]), bins=30, \n",
    "    normed=True, alpha=0.5, label='misclassification'\n",
    ");\n",
    "plt.legend();\n",
    "plt.xlabel('entropy of predictions');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### confidence of predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff2602485f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(\n",
    "    val_predictions[hits].max(1), bins=30, \n",
    "    normed=True, alpha=0.7, label='correct prediction'\n",
    ");\n",
    "plt.hist(\n",
    "    val_predictions[~hits].max(1), bins=30, \n",
    "    normed=True, alpha=0.5, label='misclassification'\n",
    ");\n",
    "plt.legend();\n",
    "plt.xlabel('confidence of predictions');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### difference between biggest and second biggest probability"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff26019dfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sorted_correct = np.sort(val_predictions[hits], 1)\n",
    "sorted_incorrect = np.sort(val_predictions[~hits], 1)\n",
    "\n",
    "plt.hist(\n",
    "    sorted_correct[:, -1] - sorted_correct[:, -2], bins=30, \n",
    "    normed=True, alpha=0.7, label='correct prediction'\n",
    ");\n",
    "plt.hist(\n",
    "    sorted_incorrect[:, -1] - sorted_incorrect[:, -2], bins=30, \n",
    "    normed=True, alpha=0.5, label='misclassification'\n",
    ");\n",
    "plt.legend();\n",
    "plt.xlabel('difference');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### probabilistic calibration of the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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UUZZ0KZ3p3+1nYWQsdauWYUA7X0oW89QkYZWVlcWiRYt4/vnnOXLkCH369GH6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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff2601d9a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model_calibration(val_true_targets, val_predictions, n_bins=10)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
